Robust interlaboratory reproducibility of a gene expression signature measurement consistent with the needs of a new generation of diagnostic tools

The increasing use of DNA microarrays in biomedical research, toxicogenomics, pharmaceutical development, and diagnostics has focused attention on the reproducibility and reliability of microarray measurements. While the reproducibility of microarray gene expression measurements has been the subject of several recent reports, there is still a need for systematic investigation into what factors most contribute to variability of measured expression levels observed among different laboratories and different experimenters.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Psoriasis prediction from genome-wide SNP profiles

<p>Abstract</p> <p>Background</p> <p>With the availability of large-scale genome-wide association study (GWAS) data, choosing an optimal set of SNPs for disease susceptibility prediction is a challenging task. This study aimed to use single nucleotide polymorphisms (SNPs) to predict psoriasis from searching GWAS data.</p> <p>Methods</p> <p>Totally we had 2,798 samples and 451,724 SNPs. Process for searching a set of SNPs to predict susceptibility for psoriasis consisted of two steps. The first one was to search top 1,000 SNPs with high accuracy for prediction of psoriasis from GWAS dataset. The second one was to search for an optimal SNP subset for predicting psoriasis. The sequential information bottleneck (sIB) method was compared with classical linear discriminant analysis(LDA) for classification performance.</p> <p>Results</p> <p>The best test harmonic mean of sensitivity and specificity for predicting psoriasis by sIB was 0.674(95% CI: 0.650-0.698), while only 0.520(95% CI: 0.472-0.524) was reported for predicting disease by LDA. Our results indicate that the new classifier sIB performs better than LDA in the study.</p> <p>Conclusions</p> <p>The fact that a small set of SNPs can predict disease status with average accuracy of 68% makes it possible to use SNP data for psoriasis prediction.</p

Diversity of human copy number variation and multicopy genes

Copy number variants affect both disease and normal phenotypic variation, but those lying within heavily duplicated, highly identical sequence have been difficult to assay. By analyzing short-read mapping depth for 159 human genomes, we demonstrated accurate estimation of absolute copy number for duplications as small as 1.9 kilobase pairs, ranging from 0 to 48 copies. We identified 4.1 million singly unique nucleotide positions informative in distinguishing specific copies and used them to genotype the copy and content of specific paralogs within highly duplicated gene families. These data identify human-specific expansions in genes associated with brain development, reveal extensive population genetic diversity, and detect signatures consistent with gene conversion in the human species. Our approach makes ∼1000 genes accessible to genetic studies of disease association

Diversity of human copy number variation and multicopy genes

Copy number variants affect both disease and normal phenotypic variation, but those lying within heavily duplicated, highly identical sequence have been difficult to assay. By analyzing short-read mapping depth for 159 human genomes, we demonstrated accurate estimation of absolute copy number for duplications as small as 1.9 kilobase pairs, ranging from 0 to 48 copies. We identified 4.1 million "singly unique nucleotide" positions informative in distinguishing specific copies and used them to genotype the copy and content of specific paralogs within highly duplicated gene families. These data identify human-specific expansions in genes associated with brain development, reveal extensive population genetic diversity, and detect signatures consistent with gene conversion in the human species. Our approach makes similar to 1000 genes accessible to genetic studies of disease association

Benign copy number changes in clinical cytogenetic diagnostics by array CGH

A database of apparently benign copy number variants (bCNVs) detected by a Spectral Genomics Inc./PerkinElmer BAC array platform has been maintained through the University of Utah Comparative Genomic Hybridization laboratory since 2005. The target population for this database represents 1,275 patients with abnormal phenotypes, primarily children referred for developmental delay and mental retardation. These bCNVs are independent of any identified copy number abnormality detected. The most common 35 bCNVs observed and their frequencies are reported here, and a subset of ten of the patients studied was evaluated on a new oligonucleotide CNV array set designed by Agilent Technologies. There was a 76% concordance of calls for these 35 bCNVs detected by both array platforms in the same patients. The higher resolution of the Agilent oligonucleotide array compared to the BAC array allowed determination of the precise breakpoints of the observed CNVs, in addition to documentation of additional CNVs of smaller sizes. As expected, observed CNVs and their frequencies were generally consistent with those of other previously published and available databases, including the Database of Genomic Variants (http://projects.tcag.ca/variation/). The availability of these data should assist other clinical laboratories in the evaluation of CNVs of unknown clinical significance